Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating condition characterized by profound, chronic fatigue that is not alleviated by rest, as well as pain, post-exertional malaise, and impairments in memory and concentration. ME/CFS affects over one million women in the United States, causing significant distress and loss of function in affected individuals and a significant financial burden on society Because the underlying pathophysiology of ME/CFS is not well-understood, there are no effective treatments developed specifically for the condition, and many patients are unsatisfied with existing treatment options. Previous research provides a strong case for inflammatory involvement in ME/CFS, though no immune factors have been consistently predictive of fatigue across studies. Conventional cross-sectional research approaches may not be sufficiently sensitive for identifying ME/CFS biomarkers in cases of low-level or atypical inflammation. We have observed that women with ME/CFS demonstrate considerable day-to-day variability in their fatigue severity, and this variability may reflect rapid shifts in underlying disease mechanisms. By viewing the daily fatigue variability as an important signal, and collecting blood samples daily, we have identified a small set of serum cytokines that are strongly correlated with changes in ME/CFS 1fatigue. In this proposed study, we plan to confirm our preliminary findings of immune-fatigue relationships in a larger sample. We will collect blood samples for 25 consecutive days in 70 women with ME/CFS, as well as 20 healthy controls and 20 active fatigue controls (individuals with hypothyroidism). Blood samples will be analyzed for 51 different immune factors associated with inflammation. In addition, participants will submit daily reports of fatigue severity on handheld computers. By analyzing fatigue scores and cytokine concentrations longitudinally, we can identify cytokines that track day-to-day fluctuations in fatigue severity. This approach will allow us to develop a physiological profile that distinguishes high fatigue days from low fatigue days, providing important information about ME/CFS mechanisms. In Aim 1, we will develop a physiological model that uses serum cytokine levels to accurately predict day-to-day fluctuations in fatigue severity. In Aim 2, we will define important ME/CFS subgroups based on cytokine-fatigue relationships. In Aim 3, we will develop a temporal pathway between immune factors and fatigue that identifies early drivers of fatigue. Additionally, we will develop a specimen bank of blood samples that can be made available to other interested researchers. Intensive longitudinal immune monitoring is a unique approach to understanding ME/CFS pathophysiology. Biomarkers revealed by this research will serve as tools in the development of ME/CFS diagnostic tests, and will provide excellent targets for developing improved therapies.